{ "_id": "6a1b19641d7bb097a0a0df16", "Package": "bean", "Type": "Package", "Title": "Data Thinning of Species Occurrences in Environmental Space", "Version": "0.2.0", "Authors@R": "c(\nperson(\"Paanwaris\", \"Paansri\",\nrole = c(\"cre\", \"aut\"),\nemail = \"paanwaris@vt.edu\",\ncomment = c(ORCID = \"0000-0001-9992-098X\")),\nperson(\"Luis E.\", \"Escobar\",\nrole = c(\"aut\", \"ctb\"),\nemail = \"escobar1@vt.edu\",\ncomment = c(ORCID = \"0000-0001-5735-2750\")))", "Maintainer": "Paanwaris Paansri ", "Description": "A suite of tools to mitigate sampling bias in species\noccurrence records by thinning data in the environmental space\n(E-space). This process can improve the accuracy and precision\nof species distribution models (SDM, also known as ecological\nniche models, ENM). The package offers a data-driven protocol\nto determine thinning parameters using kernel-density bandwidth\nselection. Two thinning methods are provided (stochastic and\ndeterministic) to reduce over-sampled environmental conditions\nand down-weight outlier observations. The name 'bean' reflects\nthe core principle of the method: each 'pod' (a grid cell in\nE-space) is allowed to contain only a limited number of 'beans'\n(occurrence points). See Silverman (1986,\nISBN:978-0-412-24620-3) and Rousseeuw and Leroy (2003,\nISBN:978-0-471-48855-2) for the underlying statistical methods.", "License": "MIT + file LICENSE", "URL": "https://github.com/paanwaris/bean,\nhttps://paanwaris.github.io/bean/", "BugReports": "https://github.com/paanwaris/bean/issues", "Encoding": "UTF-8", "LazyData": "true", "VignetteBuilder": "knitr", "Config/testthat/edition": "3", "Config/roxygen2/version": "8.0.0", "RoxygenNote": "8.0.0", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-30 17:03:53 UTC", "User": "root" }, "Author": "Paanwaris Paansri [cre, aut] (ORCID:\n), Luis E. 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environmental layers", "Visualise the raw occurrence points", "Run prepare_bean()", "Visualise the prepared points", "The shipped, pre-computed dataset" ], "created": "2026-05-30 13:50:07", "modified": "2026-05-30 13:50:07", "commits": 1 }, { "source": "environmental-thinning.Rmd", "filename": "environmental-thinning.html", "title": "Environmental thinning ", "engine": "knitr::rmarkdown", "headings": [ "Choosing an objective grid resolution", "The intuition", "Why a kernel-density bandwidth?", "Which selector?", "Computing the resolution", "Visualising the bandwidth", "Sensitivity to the selector", "Stochastic thinning", "Deterministic thinning", "Comparing the two thinned datasets", "Pairs view with plot_bean()" ], "created": "2026-05-30 13:50:07", "modified": "2026-05-30 13:50:07", "commits": 1 }, { "source": "niche-modeling.Rmd", "filename": "niche-modeling.html", "title": "Niche modeling ", "engine": "knitr::rmarkdown", "headings": [ "Fit three ellipsoids", "Visualise the 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